Iterative decoding schemes are used in a receiver in order to perform channel coding using Turbo codes or LDPC codes. However, since an M-ary QAM modulation signal in which one symbol is expressed as some bits is transmitted in symbol unit, it is inevitable that a symbol signal is converted into information in the form of bits for iterative decoding. Such conversion is accomplished by soft decoding, soft metric, Log Likelihood Ratio (LLR), soft demapping and the like.
Therefore, as will be described later, in an M-ary QAM receiving system that transmits log2M number of bits per symbol by using Gray mapping, the present invention is to convert a received symbol signal into soft bit metric information per bit (I or Q channel) and transmits the converted information to an iterative decoder such as a Turbo or LDPC decoder, as illustrated in FIG. 2.
As methods for converting a symbol signal into a bit signal, there are generally a Maximum A Posteriori (MAP) scheme and a signal space division scheme. However, since the MAP scheme is very complex in formula operation, it is advanced to a log-MAP that applies algebraic operation to MAP. And, the log-MAP is again enhanced to a Max-Log-MAP algorithm with even lower complexity in design. On the other hand, the signal space division scheme uses geometric space division formulas to divide signal space based on a constellation position of a transmitted signal. So there are many different implementation methods that are based on the signal constellation.
In general, a Look-Up Table (LUT) based method using a memory is employed to reduce implementation complexity, but it also has drawbacks in that errors may occur, and especially, when Adaptive Modulation and Coding (AMC) scheme that changes a modulation method is used, various LUTs must be provided depending on a given symbol arrangement and also be updated according to a selected modulation method.
Moreover, the conventional MAP exhibiting high-performance involves an exponential calculation, the log-MAP that is logarithmic MAP requires an exponential operation, and the Max-Log-MAP that approximates the log-MAP also has high-complexity in design. In particular, even in case of a scheme using a signal space, an LUT must be configured in accordance with a symbol arrangement.
Therefore, the iterative decoding scheme is essential for maintaining an efficient and stable communication quality in receiving a higher-order modulation signal. This iterative decoding scheme is based on binary transmission, and thus, when a higher-order modulation symbol signal is received, the symbol signal should be converted into information in the form of bits so that the receiving system can effectively employ the binary iterative decoding scheme.
Especially, the QAM decoding method is known to be the best decoding method that can most effectively use the same bandwidth. However, the QAM transmission is susceptive to the influence of fading or noises and thus requires a high Signal to Noise Ratio (SNR) to ensure stable reception. The iterative decoding scheme is useful to compensate the above shortcomings because it can acquire the high coding gain over channel coding such as Turbo codes or LDPC codes, which becomes a transmission system suitable for wideband transmission. In order to utilize the iterative decoding scheme for the higher-order modulation QAM signal, it is absolutely necessary to generate a soft bit metric that converts a transmitted symbol signal into soft bit information.
Consequently, the soft bit metric generation for the conversion of symbol-to-bit information requires a complex operation algorithm, so there is a need to develop a new scheme for reducing implementation complexity of such algorithm and generating soft bit metric information effectively.